A hierarchical network-oriented analysis of user participation in misinformation spread on WhatsApp

GP Nobre, CHG Ferreira, JM Almeida - Information Processing & …, 2022 - Elsevier
WhatsApp emerged as a major communication platform in many countries in the recent
years. Despite offering only one-to-one and small group conversations, WhatsApp has been …

“Why tag me?”: Detecting motivations of comment tagging in Instagram

J Kang, J Yoon, E Park, J Han - Expert Systems with Applications, 2022 - Elsevier
Tagging a friend in a comment is one of the main mechanisms to lead user interaction in
social media. This paper investigates the current practice of user tagging in Instagram by …

On network backbone extraction for modeling online collective behavior

CH Gomes Ferreira, F Murai, APC Silva, M Trevisan… - Plos one, 2022 - journals.plos.org
Collective user behavior in social media applications often drives several important online
and offline phenomena linked to the spread of opinions and information. Several studies …

A gradient boosted decision tree-based influencer prediction in social network analysis

N Subramani… - Big Data and Cognitive …, 2023 - mdpi.com
Twitter, Instagram and Facebook are expanding rapidly, reporting on daily news, social
activities and regional or international actual occurrences. Twitter and other platforms have …

Commenter Behavior Characterization on YouTube Channels

S Shajari, N Agarwal, M Alassad - arXiv preprint arXiv:2304.07681, 2023 - arxiv.org
YouTube is the second most visited website in the world and receives comments from
millions of commenters daily. The comments section acts as a space for discussions among …

The dark side of metaverse: A multi-perspective of deviant behaviors from PLS-SEM and fsQCA findings

C XinYing, V Tiberius, A Alnoor… - … Journal of Human …, 2024 - Taylor & Francis
The metaverse has created a huge buzz of interest because such a phenomenon is
emerging. The behavioral aspect of the metaverse includes user engagement and deviant …

SocialPET: Socially Informed Pattern Exploiting Training for Few-Shot Stance Detection in Social Media

PJ Khiabani, A Zubiaga - arXiv preprint arXiv:2403.05216, 2024 - arxiv.org
Stance detection, as the task of determining the viewpoint of a social media post towards a
target as' favor'or'against', has been understudied in the challenging yet realistic scenario …

Temporal dynamics of posts and user engagement of influencers on Facebook and Instagram

L Vassio, M Garetto, C Chiasserini… - Proceedings of the 2021 …, 2021 - dl.acm.org
A relevant fraction of human interactions occurs on online social networks. Freshness of
content seems to play an important role, with content popularity rapidly vanishing over time …

Uncovering coordinated communities on twitter during the 2020 us election

RS Linhares, JM Rosa, CHG Ferreira… - 2022 IEEE/ACM …, 2022 - ieeexplore.ieee.org
A large volume of content related to claims of election fraud, often associated with hate
speech and extremism, was reported on Twitter during the 2020 US election, with evidence …

Mining and modelling temporal dynamics of followers' engagement on online social networks

L Vassio, M Garetto, E Leonardi… - Social Network Analysis …, 2022 - Springer
A relevant fraction of human interactions occurs on online social networks. In this context,
the freshness of content plays an important role, with content popularity rapidly vanishing …